​I think it originally comes from the military, probably the US Navy SEALs, but it’s a popular trope in the racing world, and equally applicable to software development: “slow is smooth, smooth is fast”. It’s intentionally conflicting, but it succinctly states the idea that taking the time to do something well allows you to accomplish the end goal faster overall.

In autocross, it’s often the run that looks or feels slow that turns out to be fast. There are a few reasons why, and the allegory to development is not hard to see. A lack of excitement or surprises may seem slow, but it’s a sign of tight control and keeping within limits. Smooth, gentle, practiced driver inputs can appear almost casual in their ease.

On the other hand, the very active driver, who is constantly manipulating the controls and struggling to maintain control and riding the very razor’s edge of traction (or past it) appears to be fast. There’s a lot going on, a lot of action, some squealing and sliding and tire smoke. But the timer doesn’t lie: these runs are not fast. They only appear fast.

The key is separating being busy from being productive. Not only are they not the same, they’re often in direct opposition to one another. But it may be the busy team that appears productive on the surface.

The team that fills calendars with meetings and holds war room sessions and works late nights and fixes critical bugs at the last minute looks fast. They can’t waste time on careful thought or refactoring or automation, they’ve got features to ship! But it’s the team that works their eight hours each day with no fuss and no panic, that spends time on automating everything they can, that takes steps to detect and mitigate problems early, that thinks through problems and solutions before writing code, that will accomplish the most at the end of the week.

Urgency is not a requirement of productivity. Remember: slow is smooth, smooth is fast.

Go (or golang, as it is often called, because “Go” is a bit vague when typed into a search engine), if you haven’t heard of it, is a relatively new language for cross-platform development. It is a modern, C-style, statically-typed language that produces platform-native binaries, but still includes memory management and garbage collection.

Go is open-source, stable (currently at version 1.6, with its first stable release dating back to 2011), and it’s not going anywhere. Written by a couple of Google’s brilliant engineers, and used internally at Google at the levels of scale and reliability you would expect from a tech giant, it is an entirely different beast from something like Ruby or NodeJS. It encourages the kind of development and deployment pipeline that we should all strive for.

Software development has been moving more and more toward interpreted, dynamically-typed, single-threaded languages like Ruby and Node. It’s been moving more toward mountains of external dependencies – I’ve seen projects where more than 90% of the code was in third-party libraries. That’s a lot of other people’s technical debt and generalized implementations to absorb into your project.

Go encourages the exact opposite. It’s statically-typed, though it offers the convenience of type inference. It’s compiled, and not just to bytecode, but to native binary. It’s innately and intuitively concurrent. Its dependency management, like everything else about it, is intentionally minimalist, implicitly discouraging overuse of external libraries and frameworks.

Go, by design, at the language level, encourages a lot of really good programming practices:

Because the language and standard library aim for “exactly enough and no more”, developers are more likely to follow that lead with their own code. Go is the embodiment of KISS.

Go makes it easy and intuitive to handle concurrency through “communication instead of sharing”, keeping code cleaner and reducing the rate of defects. It also has a built-in race condition detector that can be activated when running tests or benchmarks.

The core Go tool chain includes support for unit tests and benchmarks, and will even include example code from your documentation to ensure it compiles and works.

Go has a language-level style guide, and included in the core Go tool chain is a tool (gofmt) that reformats files to fit the standard style.

Go omits many facets of OOP, including inheritance (though it has mix-ins), abstract classes, method overloading, operator overloading, and multi-level access control. Though useful tools in some cases, these are most frequently used to vastly over-complicate implementations. Go really wants you to just write the simplest thing that will work.

After the code is written, Go makes it very easy to set up continuous integration, including unit tests, benchmarks, linting, and test coverage. It’s trivial to have a build go on to cross-compile for every platform and architecture you might want to deploy to.

How do you deploy a Go app? Drop the executable on a server and execute it. There is no interpreter or virtual machine to install. In fact, there are no external dependencies at all unless you create them in code. Performance is excellent and resource usage is minimal – unlike, for example, Java or Ruby. The deployment footprint is about as small as it gets, and deployments are highly reliable. You suffer none of the fragility brought on by differences between versions of Java, Ruby, Python, or NodeJS – your binary runs the same regardless of the system it’s deployed to.

I won’t say that Go is perfect, or universally applicable. There are certainly use cases it is not well-suited to. For starters, Go produces console applications, not GUIs. It is not intended for building desktop applications – though there are libraries for doing so. Go also has a focus on simplicity and minimalism, and it could get difficult to manage very large code bases in Go unless you’re very careful and very smart about it.

Where Go really shines is in producing small, self-contained, single-purpose command-line tools and microservices. The Go standard library includes a multi-threaded HTTP server perfect for building a REST API server in a hurry, while still being able to stand up to production use.

Developers have a tendency to over use third party libraries. They bring them in because they want some new technical advance that’s in the spotlight – ORM or IOC or AOP. They don’t stop to consider that they’re importing all that library’s technical debt and defects, along with a black box they won’t understand when it fails.

However, there are some excellent cases for third party libraries. Unfortunately, these are the same cases w where developers tend not to reach for an outside solution; cases where developers think, hey, this is easy, I’ve got this.

The best case I can think of for a third party library is functionality that is simple, well understood, and stable, but with a lot of edge cases. The canonical example is date and time handling.

Date and time handling is easy, right? You’ve understood clocks and calendars since grade school. You even grok Unix timestamps. You could do date and time handling in your sleep, with your hands tied behind your back – if you can manage to sleep with your hands tied behind your back in the first place, but that’s neither here nor there.

But wait – you wrote this software to use the user’s local time zone with no offset. Interoperability issues ensue. OK, no big deal, time zones are tricky but they’re not rocket science. You make a fix a move on.

Damn. Daylight savings time. No one hates daylight savings time more than developers. Another patch. But wait, some places don’t do daylight savings time. Another patch. Leap years. Forgot about leap years. Another patch. But they aren’t every four years – the year 2000, for example, was not a leap year. Another patch. Wait, leap seconds? That’s a thing? OK, another patch. What do you mean different people put the day, month, and year in a different order? Alright, alright, another patch. 24-hour time? No problem, patch. Wait, is midnight 00:00 or 24:00? What if someone inputs 24:05? What if someone increments a time by 10 minutes at five till midnight? Or at 1:55 the day daylight savings starts or ends? Or before a leap second is applied? What if a user is mobile and their time zone changes while they’re using the application?

Time and date are simple, every day parts of our lives. We take them for granted. We haven’t changed the way clocks and calendars work in any significant way in our lifetimes. But they’re absolutely rife with details and complexities and edge cases that are very difficult to enumerate off the top of your head – you’re bound to miss some of them. A library is perfect for this: because the functionality doesn’t need to change, a good library will be stable, with very infrequent updates, and few defects. Why kill yourself with patch after patch when there’s bound to be a solid solution waiting out there for you to use?

These are the sorts of cases where libraries are the right answer. Not for adding new bells and whistles, but for using an existing solution to a thoroughly solved problem. Character encoding is a good case. Handling any common file format is definitely a good case – XML, JSON, YAML, CSV. If I never see another hand-written CSV parser it’ll be too soon. Sorting – for Petes sake, if your language doesn’t have sorting built in, find a library. I don’t care if you learned to write a bubble sort in college. Don’t write one at work. Ever.

Anything even remotely related to cryptography you should absolutely solve with a library. Hashing, random number generation, and encryption are solved, hard problems. Even when security isn’t critical, you may as well lean on the work of other smart people.

Solved problems are where you want a library. Solutions in search of a problem may be more exciting, and come with more interesting acronyms and blog posts and conference keynotes, but they often create at least as many problems as they solve. Don’t get sucked in.

“Code reviews are the worst! All the code I have to review is terrible, and people always take offense when I point out problems. And being reviewed is even worse – people always think they know better than I, can you believe it? And it’s all such a waste of time!”

It can be difficult to get a team started on code reviews, especially an established team without an established culture of reviews. Developers can be very defensive about their code, and often don’t see the value in code reviews. But the value is undeniable, and good developers will come to appreciate code reviews once they get used to them. Why?

Reviews reduce defects. This is the primary purpose of reviews, and they’re very effective.

Reviewing code builds familiarity for the reviewer. The reviewer is exposed to code they might not have worked with before, giving them a broader base of knowledge in their own development work.

Reviewing code improves developers ability to self-review. The more code you review, the better you get at reviewing code. The better you are at reviewing code, the better you can review your own code before you commit it. The better reviewed code is before it’s committed, the fewer defects are found in peer review, and the faster peer reviews are.

Expecting code to be reviewed encourages developers to self-review. Knowing that someone else is going to go over your changes after you submit them encourages you to self-review to save yourself the embarrassment, however slight, of a failed peer review.

Peer review improves consistency. When developers submit code without anyone else looking at it, they tend to follow their own styles and practices. As they review more of each others’ code, they will naturally tend to converge on a fairly similar set of styles and practices.

In situations where everyone is an architect – which I strongly support – peer review is even more critical. Collective design is only collective if everyone is looking over each other’s shoulders, seeing how problems are being solved, and suggesting possible alternative solutions. It really helps close the gap between a group of individuals and a true development team.

Countless tools exist for performing code reviews; the review handling built into pull requests in Atlassian’s Bitbucket and Stash is excellent, though there are many solutions, from simple things like adding a review step to your ticket workflow and putting review comments in the ticket, to using a dedicated review tool like Crucible or Reviewboard.

User experience design is a tricky thing, full of tiny, seemingly insignificant pitfalls that can end up causing major frustration for users. One common pitfall is being more precise than you are accurate. The typical example uses pi: 3 is accurate, but not precise, while 3.6789 is more precise, but less accurate. Accuracy in a system is controlled by a wide array of factors, but generally you’re aware of the limitations in place and you have a general idea of your accuracy. Precision you can control directly through interface design, so you should always have it match your accuracy, never exceed it. Any estimation, extrapolation, aggregation, or rounding can introduce a loss of precision. Digital floating point math is inherently imprecise.

Users naturally presume that any number they’re looking at is as accurate as it is precise. If you show four decimal places, they assume that number is accurate to four decimal places, and rightly so. If you show numbers in millions (37M), users will assume this is accurate to the nearest million. They naturally trust you to present them with accurate information, so they assume that whatever information they’re given is accurate. This is exactly why you should ensure that you don’t present information that you don’t know to be accurate.

You’ve built a prototype, everything is going great. All your dates and times look great, they load and store correctly, everything is spiffy. You have your buddy give it a whirl, and it works great for them too. Then you have a friend in Curaçao test it, and they complain that all the times are wrong – time zones strike again!

But, you’ve got this covered. You just add an offset to every stored date/time, so you know the origin time zone, and then you get the user’s time zone, and voila! You can correct for time zones! Everything is going great, summer turns to fall, the leaves change, the clocks change, and it all falls apart again. Now you’re storing dates in various time zones, without DST information, you’re adjusting them to the user’s time zone, trying to account for DST, trying to find a spot here or there where you forgot to account for offsets…

Don’t fall into this trap. UTC is always the answer. It is effectively time-zone-less, as it has an offset of zero and does not observe daylight savings time. It’s reliable, it’s universal, it’s always there when you need it, and you can always convert it to any time you need. Storing a date/time with time zone information is like telling someone your age by giving your birthday and today’s date – you’re dealing with additional data and additional processing with zero benefit.

When starting a project, you’re going to be better off storing all dates as UTC from the get-go; it’ll save you innumerable headaches later on. I think it is atrocious that .NET defaults to system-local time for dates; one of the few areas where I think Java has a clearly better design. .NET’s date handling in general is a mess, but simply defaulting to local time when you call DateTime.Now encourages developers to exercise bad practices; the exact opposite of the stated goals of the platform, which is to make sure that the easy thing and the correct thing are, in fact, the same thing.

On a vaguely related note, I’ve found a (in my opinion) rather elegant solution for providing localized date/time data on a website, and it’s all wrapped up in a tiny Gist for your use: https://gist.github.com/aprice/7846212

This simple jQuery script goes through elements with a data attribute providing a timestamp in UTC, and replaces the contents (which can be the formatted date in UTC, as a placeholder) with the date/time information in the user’s local time zone and localized date/time format. You don’t have to ask the user their time zone or date format.

Unfortunately it looks like most browsers don’t take into account customized date/time formatting settings; for example, on my computer, I have the date format as yyyy-mm-dd, but Chrome still renders the standard US format of mm/dd/YYYY. However, I think this is a relatively small downside, especially considering that getting around this requires allowing users to customize the date format, complete with UI and storage mechanism for doing so.

I’ve been seeing a lot of posts lately on code comments; it’s a debate that’s raged on for ages and will continue to do so, but for some reason it’s been popping up in my feeds more than usual the last few days. What I find odd is that all of the posts generally take on the same basic format: “on the gradient of too many to too few comments, you should aim for this balance, in this way, don’t use this type of comments, make your code self-documenting.” The reasoning is fairly consistent as well: comments get stale, or don’t add value, or may lead developers astray if they don’t accurately represent the code.

And therein lies the rub: they shouldn’t be representing the code at all. Code – clean, self-documenting code – represents itself. It doesn’t need a plain-text representative to speak on its behalf unless it’s poorly written in the first place.

It may sound like I’m simply suggesting aiming for the “fewer comments” end of the spectrum, but I’m not; there’s still an entity that may occasionally need representation in plain text: the developer. Comments are an excellent way to describe intent, which just so happens to take a lot longer to go stale, and is often the missing piece of the puzzle when trying to grok some obscure or obtuse section of code. The code is the content; the comments are the author’s footnotes, the director’s commentary.

Well-written code doesn’t need comments to say what it’s doing – which is just as well since, as so many others have pointed out, those comments are highly likely to wind up out-of-sync with what the code is actually doing. However, sometimes – not always, maybe even not often, but sometimes – code needs comments to explain why it’s doing whatever it’s doing. Sure, you’re incrementing Frobulator.Foo, and everybody is familiar with the Frobulator and everybody knows why Foo is important and anyone looking at the code can plainly see you’re trying to increment it. But why are you incrementing it? Why are you incrementing it the way you’re doing it in this case? What is the intent, separate from its execution? That’s where comments can provide value.

As a side note (no pun intended), I hope we can all agree that doc comments are a separate beast entirely here. Doc comments provide meta data that can be used by source code analyzers, prediction/suggestion/auto-completion engines, API documentation generators, and the like; they provide value through some technical mechanism and are generally intended for reading somewhere else, not for reading them in the source code itself. Because of this I consider doc comments to be a completely separate entity, that just happen to be encoded in comment syntax.

My feelings on doc comments are mixed; generally speaking, I think they’re an excellent tool and should be widely used to document any public API. However, there are few things in the world more frustrating that looking up the documentation for a method you don’t understand, only to find that the doc comments are there but blank (probably generated or templated), or are there but so out of date that they’re missing parameters or the types are wrong. This is the kind of thing that can have developers flipping desks at two in the morning when they’re trying to get something done.